Design, implement, and deploy AI-powered features, including model training, fine-tuning, and prompt engineering workflows.
Translate product requirements into robust, production-ready AI solutions, working with Product Managers, Software Engineers, and Data Scientists.
Optimize models and infrastructure for scalability, latency, and cost efficiency, partnering with DevOps and MLOps to ensure reliable and maintainable AI pipelines.
Design, build, and productionize ML models for fine-tuned, Retrieval-Augmented Generation (RAG), and generative AI features.
Build and maintain scalable data pipelines to collect high-quality training and evaluation datasets, including annotation systems and human-in-the-loop workflows.
Collaborate with product and engineering to iterate on datasets, evaluation metrics, and model architectures to improve quality and relevance.